According to @godofprompt, the RTL model demonstrates a significant breakthrough by requiring 10x fewer parameters than independent models while delivering higher accuracy compared to single-mask approaches. This innovation is effective across diverse domains, including vision, speech, and coordinate-based representations. At 75% sparsity, RTL outperforms all baselines, utilizing only 38,000 parameters versus 314,000 required by traditional models, as reported by @godofprompt.